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From Abstract Task Knowledge to Executable Robot Programs

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Abstract

Robots that are capable of learning new tasks from humans need the ability to transform gathered abstract task knowledge into their own representation and dimensionality. New task knowledge that has been collected e.g. with Programming by Demonstration approaches by observing a human does not a-priori contain any robot-specific knowledge and actions, and is defined in the workspace of the human demonstrator. This article presents a new approach for mapping abstract human-centered task knowledge to a robot execution system based on the target system properties. Therefore the required background knowledge about the target system is examined and defined explicitly.

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Authors and Affiliations

  1. Industrial Applications of Computer Science and Micro Systems (IAIM), Institute of Computer Science and Engineering (CSE), University of Karlsruhe (TH), Haid-und-Neu-Straße 7, 76131, Karlsruhe, Germany

    Steffen Knoop, Michael Pardowitz & Rüdiger Dillmann

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  1. Steffen Knoop
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  2. Michael Pardowitz
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  3. Rüdiger Dillmann
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Correspondence to Steffen Knoop.

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Knoop, S., Pardowitz, M. & Dillmann, R. From Abstract Task Knowledge to Executable Robot Programs. J Intell Robot Syst 52, 343–362 (2008). https://doi.org/10.1007/s10846-008-9221-x

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